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Proceedings Paper

Using short-wave infrared imaging for fruit quality evaluation
Author(s): Dong Zhang; Dah-Jye Lee; Alok Desai
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Paper Abstract

Quality evaluation of agricultural and food products is important for processing, inventory control, and marketing. Fruit size and surface quality are two important quality factors for high-quality fruit such as Medjool dates. Fruit size is usually measured by length that can be done easily by simple image processing techniques. Surface quality evaluation on the other hand requires more complicated design, both in image acquisition and image processing. Skin delamination is considered a major factor that affects fruit quality and its value. This paper presents an efficient histogram analysis and image processing technique that is designed specifically for real-time surface quality evaluation of Medjool dates. This approach, based on short-wave infrared imaging, provides excellent image contrast between the fruit surface and delaminated skin, which allows significant simplification of image processing algorithm and reduction of computational power requirements. The proposed quality grading method requires very simple training procedure to obtain a gray scale image histogram for each quality level. Using histogram comparison, each date is assigned to one of the four quality levels and an optimal threshold is calculated for segmenting skin delamination areas from the fruit surface. The percentage of the fruit surface that has skin delamination can then be calculated for quality evaluation. This method has been implemented and used for commercial production and proven to be efficient and accurate.

Paper Details

Date Published: 3 February 2014
PDF: 9 pages
Proc. SPIE 9025, Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, 90250B (3 February 2014); doi: 10.1117/12.2045406
Show Author Affiliations
Dong Zhang, Sun Yat-Sen Univ. (China)
Dah-Jye Lee, Brigham Young Univ. (United States)
Alok Desai, Brigham Young Univ. (United States)


Published in SPIE Proceedings Vol. 9025:
Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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